After a long research effort, I built a SAST scanner that matches CodeQL's detection with 3× fewer false positives. Strong signal, or not enough to judge a scanner?

📰 Reddit r/learnprogramming

Build a SAST scanner with reduced false positives and evaluate its performance against industry standards like CodeQL

advanced Published 11 Jun 2026

Action Steps

Build a SAST scanner using a programming language like Python or C++
Run the scanner on a public benchmark with labelled ground truth to evaluate its performance
Compare the results with industry standards like CodeQL to measure false positives and true vulnerabilities detected
Configure the scanner to optimize its detection algorithms and reduce false positives
Test the scanner on various codebases to ensure its accuracy and reliability

Who Needs to Know This

Security engineers and developers can benefit from this knowledge to improve their vulnerability detection tools and reduce false positives, making their workflows more efficient

Key Insight

💡 Reducing false positives in SAST scanners is crucial for efficient vulnerability detection and triage

Key Takeaways

Build a SAST scanner with reduced false positives and evaluate its performance against industry standards like CodeQL

Full Article

I built a full SAST scanner that performs both vulnerability detection and triage. The goal is to reduce false positives without dropping real vulnerabilities. To evaluate it, I ran it head-to-head against CodeQL on a public benchmark with labelled ground truth. Both tools detected every labelled vulnerability in the benchmark, while mine produced roughly 3× fewer false positives: Tool

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